The field of the invention relates generally methods and apparatus for integrating model data from native tool formats into a common semantic representation, and more particularly such methods and applications that allow sharing of models between disparate engineering tools.
Improved performance of real time Health Management (HM) and maintenance functions is becoming a primary design goal of complex systems. Legacy approaches to system design, which focused primarily on minimizing initial acquisition costs, have been generally inadequate to address availability-driven design. While tools that support availability modeling are not new, traditional acquisition processes have not generally emphasized their importance, and attempts to include availability as a primary design metric have often been met with resistance.
A common way to represent system behavior is to create a model of that behavior. Modeling approaches vary considerably—their usefulness is proportional to the degree to which they can represent interesting aspects of system behavior in a way that reduces or abstracts the complexities of collateral behavior. There are many categories of models; mental, physical, verbal, etc. In engineering applications, both qualitative (descriptive) and quantitative (mathematical) models, which may take various forms (e.g., text, spreadsheets, graphical representations, static or dynamic networks, etc.), are often employed. In general, models support analyses of important aspects of system behavior and enable dynamic views of that behavior via calculation, visualization, simulation, etc. Correctly designed models allow engineers and analysts to draw conclusions and predictions of system behavior in ways otherwise unattainable, as well as to represent their own knowledge of the system and its characteristic properties.
Integrated Vehicle Health Management (IVHM) is a technology and process that allows operators to move from maintenance action to management by providing intelligent decision support re system operational responsiveness. IVHM also improves turnaround time through more accurate and timely fault reporting, simplified diagnostics, and efficient, proactive management of repairs. IVHM may also reduce preventative maintenance and inspections, improve safety, and increase the user's confidence in system reliability. The result is a safer, more affordable system with increased availability.
IVHM systems usually comprise a plurality of modeling, analysis, and reasoning tools to represent a system such as, for example, an aircraft. Certain modeling tools may have a closely coupled diagnostic reasoner. However, costs associated with IVHM application development are high because of inherent synchronization problems of concurrently maintaining different configurations of these models within each engineering application, i.e., independent copies of models that contain a large amount of overlapping data.
So, even in cases where direct information exchange between tools may be attempted, such closely coupled approaches to model exchange as described above suffer from several limitations:
1. Semantic rules and consistency must be guaranteed at the exchange level and maintained at the processing level by “hard-wiring” connections into the body of the code that performs the information exchange and processing. Such an approach is extremely brittle to errors in assumptions or changes in the information and specific application formats to be shared between interoperating applications. If errors or changes occur, it requires a significant effort to analyze and incorporate the ramifications of these anomalies into the translation process.
2. Developing translators for each pair of tools that need to share data can result in the creation and maintenance of O(n2) translators.
3. Pair-wise tool coupling does not support the cumulative knowledge creation effect of multiple tools contributing to a single integrated model of engineering knowledge.
Typically, code based translations have to take into account data format and syntactic issues as well as required “semantic” transforms to correctly translate information from one application to another. Inter-mixing the logic for the syntactical, data format translations with that required semantic transformations between two information sources make the transforms more difficult to create, prone to error in development, and brittle to maintain.